Wajid Ali | Technology Management | Emerging Research Star Award

Posted on by ScienceFather

Wajid Ali | Technology Management | Emerging Research Star Award

Lecturer at International Islamic University Islamabad Pakistan

Dr. Wajid Ali is an emerging scholar in Technology Management with an interdisciplinary background in engineering and management sciences. With a PhD in Management Sciences (Technology Management) from the International Islamic University, Islamabad (2025), Dr. Ali has made significant research contributions in the domain of Artificial Intelligence (AI) readiness, organizational performance, and innovation strategy. His scholarly work spans over seven peer-reviewed publications and systematic literature reviews, highlighting his deep commitment to bridging engineering principles with management innovation. Beyond academia, Dr. Ali’s professional journey includes hands-on industrial experience in mechanical maintenance and instructional roles in top Pakistani universities. His blend of academic prowess and technical expertise makes him a rising leader in AI-based transformation in public and private sectors. A strong advocate for interdisciplinary growth, he continues to contribute to research and teaching that advances technology-driven management solutions for emerging economies.

Publication Profile

Google Scholar

Education

Dr. Wajid Ali holds a Ph.D. in Management Sciences with a focus on Technology Management from the International Islamic University, Islamabad (2025), where he maintained a CGPA of 3.50/4.00. He earned his MS in Engineering Management from The University of Lahore in 2019 with a CGPA of 3.40/4.00 and a B.Sc. in Mechanical Engineering & Technology in 2016. Earlier, he completed a D.A.E in Mechanical Technology from the Punjab Board of Technical Education in 2012 with a commendable 75% and received a Diploma in Computer Science in 2011 with an 81% score. He also cleared the Class Three Boiler Engineer examination in 2018 and obtained his SSC (Science Group) in 2009. This solid academic foundation across engineering, management, and computing reflects Dr. Ali’s diverse capabilities and underpins his research in AI-driven technological innovation and efficiency in organizations.

Experience

Dr. Wajid Ali has over six years of professional experience blending academia and industry. He has served as a visiting lecturer at the International Islamic University Islamabad and Fatima Jinnah Women’s University Rawalpindi for two years, where he taught across Management Sciences, Engineering, and Social Sciences. His responsibilities extended to administrative duties, test supervision, seminar organization, and curriculum planning. Additionally, Dr. Ali boasts 3 years and 8 months of practical experience as a mechanical maintenance technician. His industrial tenure includes critical outage projects at renowned power plants like Kot Addu Power Company (KAPCO), Roush Power Plant, Fuji Kabir Wala Power Plant, and others. From 2016 to 2018, he was engaged in operational and maintenance roles at SKAIKHU Sugar Mills LTD. His internships at KAPCO and GENCO-3 further enriched his engineering experience. This multidisciplinary exposure shapes his innovative and grounded research in AI readiness and performance optimization.

Awards and Honors

While formal awards have not been explicitly listed in his profile, Dr. Wajid Ali’s rapid progression through academic ranks, strong publication record, and diverse professional experience are indicative of his emerging stature in the field of technology management research. He has gained recognition through publication in reputed journals such as Data Science and Management, Journal of Business and Management Research, and International Journal of Business and Management Sciences. His contribution as a co-author in collaborative research projects reflects his growing academic network and influence. His teaching roles at top institutions and involvement in cross-functional academic initiatives also highlight institutional trust in his expertise. Given his Ph.D. completion in 2025 and multiple publications during the doctoral phase, Dr. Ali is a compelling candidate for the Emerging Research Star Award, which aims to celebrate promising early-career researchers who demonstrate leadership and innovation potential.

Research Focus

Dr. Wajid Ali’s research centers on Artificial Intelligence (AI) Readiness, Technology Management, and Organizational Performance. His investigations aim to uncover how public sector and transformational organizations can strategically prepare for and leverage AI integration. Through expert surveys, literature reviews, and empirical models, he explores critical success factors influencing AI adoption, cost efficiency, and the mediating role of control systems. His work also delves into emotional intelligence, team dynamics, and their impact on project success—bridging human factors with technological transitions. Dr. Ali’s interdisciplinary approach combines engineering management tools with data-driven strategic planning. His growing body of work addresses both theoretical frameworks and practical challenges facing institutions undergoing digital transformation. As organizations worldwide increasingly adopt AI, Dr. Ali’s research offers timely, actionable insights into readiness metrics, cost control, and innovative strategies that optimize performance in both emerging and established economies.

Publication Top Notes

Laws Governed Role Of Artificial Intelligence And Machine Learning In Supply Chain Management

Factors influencing readiness for artificial intelligence: a systematic literature review

THE DETERMINANTS OF CONSUMERS’ONLINE SHOPPING BEHAVIOUR: AN EMPIRICAL ASSESSMENT

Empowering Small and Medium Enterprises Performance Through Dynamic Marketing Strategies and Innovations

The influence of emotional intelligence and team building on project success

Exploring Artificial Intelligence Readiness Framework for Public Sector Organizations: An Expert Opinion Methodology

Assessment of community perceptions on drinking water quality and its implications for human health in Islamabad, Pakistan: A comprehensive analysis

Critical Artificial Intelligence Readiness Factors in Context of Public Sector Organizations: An Expert Opinion Survey

Shuai Cao | Computer Science and Artificial Intelligence | Best Researcher Award

Posted on by ScienceFather

Shuai Cao | Computer Science and Artificial Intelligence | Best Researcher Award

Dr Shuai Cao, School of Automation, Wuhan University of Technology, China

Dr. Shuai Cao is a dynamic researcher in the field of Computational Intelligence, currently pursuing graduate studies at Kunming University of Science and Technology and engaging in joint research at the Guangdong Academy of Sciences. With a focus on enhancing meta-heuristic algorithms, Dr. Cao has contributed significantly to engineering optimization, especially in AGV path planning and offset printing machine design. He is the mind behind the innovative Piranha Foraging Optimization Algorithm (PFOA) and co-author of several impactful SCI/EI publications. His expertise in algorithm improvement, machine learning, and pattern recognition is reflected through funded projects and hands-on roles in top research institutions like the South China Intelligent Robot Innovation Institute. With a remarkable blend of theoretical insight and practical application, Dr. Cao is a promising candidate for the Best Researcher Award, embodying academic rigor and real-world impact.

Publication Profile 

Orcid

Education

Dr. Shuai Cao’s academic journey began at Baotou Rare Earth High-tech No. 1 High School (2014–2017), where he laid a strong foundation in the sciences. He pursued his undergraduate degree in Mechanical and Electronic Engineering at Chongqing University of Humanities, Science and Technology (2017–2021), gaining critical insights into systems design and robotics. Since 2021, he has been a postgraduate student in Electronic Information at Kunming University of Science and Technology, further sharpening his expertise in computational theory and algorithmic systems. Complementing his studies, Dr. Cao has been engaged in a joint training program at the Intelligent Manufacturing Institute of the Guangdong Academy of Sciences since 2022. His coursework includes meta-heuristic algorithms, machine learning, digital signal processing, and pattern recognition, all of which feed directly into his research in Computational Intelligence and engineering optimization. His interdisciplinary background empowers him to tackle complex problems with innovative solutions.

Experience

Dr. Shuai Cao has held impactful roles in prestigious research institutions. From May 2022 to July 2023, he worked at the Intelligent Manufacturing Institute of the Guangdong Academy of Sciences, where he conducted advanced research on AGV handling robots. This included applying improved intelligent algorithms for path planning and optimization scheduling—work closely aligned with his master’s thesis. Since July 2023, he has been with the South China Intelligent Robot Innovation Institute, applying swarm intelligence methods to optimize the structure of high-speed multi-color offset printing machines. Dr. Cao’s work integrates theoretical research with industrial application, setting a benchmark for practical relevance. His involvement in key science and innovation projects also reflects his growing leadership in the field. From optimization algorithms to real-world robotic systems, Dr. Cao’s hands-on approach is shaping the future of intelligent manufacturing.

Awards and Honors

Dr. Shuai Cao has earned distinguished recognition in both academic and research circles for his innovative contributions to engineering optimization. As a lead researcher on multiple government-funded projects—including “Research and Application of Intelligent Scheduling of Mobile Collaborative Robot Clusters for Intelligent Manufacturing” (Project Code: 2130218003022) and the “Foshan Science and Technology Innovation Team Project” (Project Code: FS0AA-KJ919-4402-0060)—he has demonstrated expertise in bridging theory with practical industrial solutions. His pioneering research has been published in high-impact SCI and EI journals and conferences, such as IEEE ACCESS and the International Conference on Robotics and Automation Engineering (ICRAE). A highlight of his work is the development of the Piranha Foraging Optimization Algorithm (PFOA), which has garnered considerable attention in the optimization community for its novelty and effectiveness. Dr. Cao’s sustained dedication to cutting-edge innovation, along with his leadership in collaborative, cross-disciplinary projects, makes him a compelling nominee for the Best Researcher Award.

Research Focus

Dr. Shuai Cao’s research is centered on Computational Intelligence, specifically the improvement and engineering application of swarm intelligence algorithms. His work addresses key challenges in traditional optimization methods, such as premature convergence, low population diversity, and slow optimization speeds. He has successfully designed algorithms that overcome these limitations, notably the Piranha Foraging Optimization Algorithm (PFOA). His research extends to practical applications like automated guided vehicle (AGV) path planning, scheduling in smart factories, and mechanical structure optimization for high-speed printing systems. Through interdisciplinary methods, he combines machine learning, pattern recognition, and digital signal processing to bring theoretical advancements into real-world manufacturing challenges. With a clear aim of enhancing intelligent manufacturing systems, his research contributes to both academic knowledge and industrial innovation. His growing body of work reflects originality, technical rigor, and a strong alignment with modern engineering demands.

Publication Top Notes

Research on the Design and Application of Multi-Port Energy Routers

 

Todor Todorov | Engineering and Technology | Best Researcher Award

Posted on by ScienceFather

Todor Todorov | Engineering and Technology | Best Researcher Award

Todor Todorov, Technical University of Sofia, Bulgaria

Prof. Dr. Todor Todorov 🎓🔬 is a distinguished researcher and professor at the Technical University of Sofia, specializing in Microelectromechanical Systems (MEMS) and Mechanism and Machine Theory. 🏛️ He has served as Head of the Laboratory of MEMS and former Dean of the Faculty of Industrial Technology. His research focuses on electromechanical devices, energy harvesting, and smart materials. ⚙️📡 With a Ph.D. in Mechanism Synthesis and an MSc in Decision Support Systems, he has led multiple national and international projects. 📚🛠️ A prolific author and editorial board member, he significantly contributes to advanced engineering innovations. 🚀💡

Publication Profile

Orcid

Education

Prof. Dr. Todor Todorov 🎓🔧 is an esteemed mechanical engineer and researcher specializing in precision engineering, decision support systems, and microelectromechanical systems. He earned his Ph.D. from the Technical University of Sofia (1992-2001) and an M.Sc. in Decision Support Systems from the University of Sunderland (1993-1994). With a career spanning academia and research, he has held leadership roles, including Deputy Head of the Department of Theory of Mechanisms and Machines and Chairman of the General Assembly of the Faculty of Industrial Technology. 📚🛠️ A prolific editor and reviewer, he contributes to multiple international journals and MDPI publications. ✍️📖

Experience

Prof. Dr. Todor Todorov is a distinguished academic at the Technical University of Sofia 🇧🇬, specializing in Microelectromechanical Systems (MEMS) and Mechanism and Machine Theory ⚙️. Since 2022, he has led the Laboratory of MEMS, previously serving as Dean of the Faculty of Industrial Technology (2019-2022) 🏫. A professor since 2013, he has taught MEMS, Microtechnology, and Machine Theory 📚. His research spans mechanism synthesis, electromechanical devices, and nanoengineering 🔬. Earlier roles include Associate Professor (2002-2013), Head Assistant Professor (1999-2002), and Senior Assistant Professor (1988-1999). Notably, he also served as Mayor of Vladaya (1995-1999) 🏛️.

Research Focus

Prof. Dr. Todor Todorov’s research focuses on vibrational energy harvesting, microcantilever sensors, and shape memory alloy (SMA)-based actuators ⚙️🔬. His work explores self-excited thermomechanical oscillators 🔥 and bistable pumps 💧 using SMAs, enhancing energy efficiency and control in microdevices. He also investigates virus and pathogen detection 🦠 with dual-microcantilever sensors and the influence of Lorentz forces on sensor sensitivity ⚡. His interdisciplinary research integrates mechanical dynamics, thermoelectromechanical systems, and ultralow mass detection 🎯. With applications in energy harvesting, biomedical sensing, and microfluidics, his studies contribute to innovative sensing technologies and efficient actuator designs for advanced engineering solutions 🚀.

Publication Top Notes

Dynamics of a Self-Excited Vibrating Thermal Energy Harvester with Shape Memory Alloys and PVDF Cantilevers

Evaluation of the Influence of Lorentz Forces on the Natural Frequencies of a Dual-Microcantilever Sensor for Ultralow Mass Detection

Investigating a Detection Method for Viruses and Pathogens Using a Dual-Microcantilever Sensor

Study of Self-Excited Thermomechanical Oscillator with Shape Memory Alloys

Study of Self-Excited Thermomechanical Oscillator with Shape Memory Alloys

Synthesis of a Bistable Recuperative Pump Powered by Shape Memory Alloys and a Two-Section Involute Cam

Linear Interval Approximation of Sensor Characteristics with Inflection Points

A Study of a Bistable Reciprocating Piston Pump Driven by Shape Memory Alloys and Recuperative Springs

Kaimin Wei | Computer Science and Artificial Intelligence | Best Researcher Award

Posted on by ScienceFather

Kaimin Wei | Computer Science and Artificial Intelligence | Best Researcher Award

Prof Kaimin Wei, Jinan University, China

Kaimin Wei is a full professor at the College of Information Science and Technology, Jinan University, China 🇨🇳. He earned his Ph.D. in Computer Science from Beihang University (2015), Master’s in Computer Application Technology from Zhengzhou University (2010), and Bachelor’s in Computer Science from Yuncheng University (2007) 🎓. A distinguished Young Pearl River Scholar 🌟, his research focuses on mobile computing, edge intelligence, and AI security 📱🤖🔒. Prof. Wei has published extensively in top journals and conferences, contributing to advancements in algorithm optimization and security techniques 📊📚.

Publication Profile

Orcid

Academic Background 

Prof. Kaimin Wei 🌟 holds a Ph.D. in Computer Science from Beihang University (2015) 🎓, a Master’s degree from Zhengzhou University (2010) 📚, and a Bachelor’s from Yuncheng University (2007) 🎯. His academic journey showcases dedication and excellence in the field of computer science 💻. Recognized for his outstanding achievements, he was honored as a Young Pearl River Scholar 🌊, reflecting his leadership potential and scholarly impact. Prof. Wei’s contributions to academia continue to inspire, highlighting his commitment to research, innovation, and education 🚀

Research Interests 

Prof. Kaimin Wei is a distinguished expert in Mobile Computing 📱, specializing in Edge Intelligence 🌐 and Artificial Intelligence Security 🔐. His research focuses on enhancing the efficiency and security of mobile technologies, leveraging cutting-edge edge intelligence to optimize data processing and real-time decision-making. Prof. Wei’s work in AI security ensures robust protection against emerging cyber threats, contributing to the development of safer, smarter digital ecosystems. His innovative approach bridges the gap between mobile computing and advanced AI applications, driving technological progress and shaping the future of secure, intelligent systems. 🚀🤖

Research Focus

Prof. Kaimin Wei’s research focuses on privacy-preserving technologies, federated learning, mobile crowdsensing, and cybersecurity 🔐📡. His work explores UAV crowdsensing with energy efficiency, gradient inversion attacks in federated learning without prior knowledge, and group task recommendations using neural collaborative approaches 🤖✨. He also investigates secure device pairing through acceleration-based methods with visual tracking and develops robust defense mechanisms against adversarial attacks using feature purification networks 🛡️📊. Prof. Wei’s interdisciplinary research blends Internet of Things (IoT), machine learning, and security protocols to enhance data privacy and system resilience 🌍🔍.

Publication Top Notes

PD-DRL: Towards privacy-preserving and energy-sustainable UAV crowdsensing

GI-SMN: Gradient Inversion Attack Against Federated Learning Without Prior Knowledge

Group Task Recommendation in Mobile Crowdsensing: An Attention-Based Neural Collaborative Approach

Attacks on Acceleration-Based Secure Device Pairing With Automatic Visual Tracking

FePN: A robust feature purification network to defend against adversarial examples

A Survey of Sparse Mobile Crowdsensing: Developments and Opportunities

Automatic Tagging by Leveraging Visual and Annotated Features in Social Media

chen yan | Engineering and Technology | Best Researcher Award

Posted on by ScienceFather

chen yan | Engineering and Technology | Best Researcher Award

Dr chen yan, Shantou Polytechnic, China

Dr. Chen Yan 🎓 is a dedicated researcher in Structural Engineering, holding a Ph.D. from Shantou University 🏗️. Currently a Postdoc at Shantou University and a Lecturer at Shantou Polytechnic 📚, Dr. Chen specializes in foamed concrete modification, geopolymer materials, and building sustainability 🌱. With numerous journal publications 📄, patents ⚙️, and leadership in scientific projects 🔬, he has guided students to win prestigious competitions 🏆. Honored as a “Shantou Youth Skilled Expert” in 2021 🌟, his work bridges academic excellence and practical innovation in civil engineering 🏢.

Publication Profile

Scopus

Education Background 

Dr. Chen Yan 🎓 is a dedicated scholar in Civil and Environmental Engineering. Currently a Postdoctoral Researcher at Shantou University 🏫 (since December 2024), Dr. Yan earned a Ph.D. in Structural Engineering (2015–2024) and a Master’s in the same field (2010–2013) from Shantou University, Guangdong, China 🌏. His academic journey began with a Bachelor’s in Civil Engineering from Hebei Normal University of Science & Technology (2005–2009) 🏗️. With a strong foundation in structural engineering, Dr. Yan focuses on innovative research, contributing to advancements in civil infrastructure and environmental sustainability 🌱🔬.

Experience

Dr. Chen Yan has been a dedicated Lecturer at Shantou Polytechnic, Guangdong, China, since July 2013 📚. She teaches courses like “G101 Flat Method Drawing and Detail Application” and “Building Mechanics and Structure” 🏗️. As a first advisor, she guided students to win prestigious awards, including the Grand Award and “Excellent Advisor Award” at the 15th “Challenge Cup” in 2019 🏆. She also mentored projects under the “Climbing Plan” and secured Innovation Awards in entrepreneurship competitions 💡. Earlier, she served as Assistant Project Manager at Dongguan Fuying Real Estate Co., Ltd. (2009–2010), assisting with construction applications 🏢.

Awards 

Dr. Chen Yan 🏅 was honored with the title of “Shantou Youth Skilled Expert” for the 2020-2021 period in recognition of exceptional expertise and contributions. In July 2023, Dr. Yan successfully presided over the application for the “Off-campus Practical Teaching Demonstration Base for Engineering Cost Major” in collaboration with Jichuanying Ancient Building Construction Co., Ltd. 🏗️ This initiative received official certification from the Guangdong Provincial Department of Education 🎓, highlighting Dr. Yan’s dedication to enhancing practical teaching and promoting academic-industry integration. 🌟

Research Interests 

Dr. Chen Yan specializes in foamed concrete modification research 🧪🏗️, focusing on enhancing the performance of cementitious materials. His work includes the analysis of micro-properties of these materials 🔬, providing insights into their structural behavior. He also utilizes numerical simulation techniques 💻 to predict and optimize the performance of cementitious composites. Dr. Yan’s research extends to innovative geopolymer materials 🌍, promoting eco-friendly construction solutions. Additionally, he is dedicated to advancing building energy efficiency and sustainability 🌱🏢, contributing to greener and more energy-efficient architectural designs. His multidisciplinary approach drives innovation in modern construction technologies. 🚀

Project Leadership

Dr. Chen Yan’s research focuses on material performance improvement and vocational education strategies. 🧪🔬 In the field of materials science, Dr. Chen explores innovative techniques to enhance material durability, efficiency, and sustainability, contributing to advancements in industrial applications. ⚙️🌍 Simultaneously, Dr. Chen is dedicated to improving vocational education, developing strategies to align technical skills with evolving industry demands. 🎓📚 His work bridges the gap between scientific innovation and practical workforce development, ensuring that both materials and human resources achieve optimal performance. 🚀🤝 Through government-funded projects, Dr. Chen fosters growth in both technology and education sectors. 💼🔍

Research Focus

Dr. Chen Yan’s research focuses on materials science and civil engineering 🏗️🔬. Specializing in the preparation and properties of wollastonite-microfiber-modified foamed concrete 🧪🧱, Dr. Yan explores advanced construction materials to enhance mechanical strength, durability, and thermal insulation 🌡️⚡. The work emphasizes optimizing foamed concrete with wollastonite microfibers to improve structural performance, lightweight applications, and eco-efficiency 🌍♻️. This research contributes significantly to sustainable building technologies, offering innovative solutions for modern construction projects 🏢🚀. Dr. Yan’s studies bridge the gap between material innovation and real-world construction needs, promoting resilience and sustainability in infrastructure development 🌆🏞️.

Publication Top Notes

Preparation and properties of wollastonite-microfiber-modified foamed concrete